Systematic Construction and Validation of a Novel Macrophage Differentiation-Associated Prognostic Model for Clear Cell Renal Cell Carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35774505", "kind": "science-record", "revision": 4, "content_hash": "sha256:cfec0b258e940f4f17548bac34d93d5af1011ef0fbe038fb8d0fd72a9f3cd23a", "created_at": "2026-11-01T18:14:48Z", "updated_at": "2026-11-01T22:06:55Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Systematic Construction and Validation of a Novel Macrophage Differentiation-Associated Prognostic Model for Clear Cell Renal Cell Carcinoma.", "doi": "10.3389/fgene.2022.877656", "pmid": "35774505", "authors": ["Chen Liu", "Xuhui Zhang", "Caoyang Hu", "Xuezhi Liang", "Xiaoming Cao", "Dongwen Wang"], "journal": "Frontiers in genetics", "year": 2022, "abstract": "Background: Clear cell renal cell carcinoma (ccRCC) is a malignant tumor of the human urinary system. Macrophage differentiation is associated with tumorigenesis. Therefore, exploring the prognostic value of macrophage differentiation-associated genes (MDGs) may contribute to better clinical management of ccRCC patients. Methods: The RNA sequence data of ccRCC were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed MDGs were unveiled in ccRCC and normal samples. The prognostic model was established according to the univariate and multivariate Cox regression analyses. By combining clinico-pathological features and prognostic genes, a nomogram was established to predict individual survival probability. The Tumor Immune Estimation Resource (TIMER) database was utilized to analyze the correlation between prognostic genes and immune infiltrating cells. Eventually, the mRNA and protein expression levels of prognostic genes were verified. Results: A total of 52 differentially expressed prognosis-related MDGs were identified in ccRCC. Afterward, a six-gene prognostic model (ABCG1, KDF1, KITLG, TGFA, HAVCR2, and CD14) was constructed through the Cox analysis. The overall survival in the high-risk group was relatively poor. Moreover, the risk score was identified as an independent prognostic factor. We constructed a prognostic nomogram with a well-fitted calibration curve based on risk score and clinical data. Furthermore, the prognostic genes were significantly related to the level of immune cell infiltration including B cells, CD8+T cells, CD4+T cells, macrophages, neutrophils, and dendritic cells. Finally, the mRNA expression of prognostic genes in clinical ccRCC tissues showed that the ABCG1, HAVCR2, CD14, and TGFA mRNA in tumor samples were increased compared with the adjacent control tissue samples, while KDF1 and KITLG were decreased, which was consistent with the verification results in the GSE53757. Conclusion: In conclusion, this study identified and validated a macrophage differentiation-associated prognostic model for ccRCC that could be used to predict the outcomes of the ccRCC patients.", "claims": [{"id": "claim-method", "statement": "The prognostic model was established according to the univariate and multivariate Cox regression analyses.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35774505", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The prognostic model was established according to the univariate and multivariate Cox regression analyses."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. These data can be found here: https://portal.gdc.cancer.gov/ https://dcc.icgc.org/ https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE53757.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35774505", "locator": "sections[23] \"Data Availability Statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. These data can be found here: https://portal.gdc.cancer.gov/ https://dcc.icgc.org/ https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE53757."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A six-gene prognostic model (ABCG1, KDF1, KITLG, TGFA, HAVCR2, and CD14) was constructed through the Cox analysis.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35774505", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The RNA sequence data of ccRCC were obtained from The Cancer Genome Atlas (TCGA) database."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A six-gene prognostic model (ABCG1, KDF1, KITLG, TGFA, HAVCR2, and CD14) was constructed through the Cox analysis.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35774505"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE53757"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE53757"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35774505", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fgene.2022.877656", "sha256": "sha256:ed5654ed75e41721d5723cfbab2d039886f1027b74e37b689e32a07625f23591", "bytes": 49848, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fgene.2022.877656", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9237391", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE53757", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE53757", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE53757", "version": null, "note": "Publicly available datasets were analyzed in this study. 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